dynamicpv: Evaluate present values and cost-effectiveness with dynamic pricing and uptake

The goal of dynamicpv is to evaluate present values and cost-effectiveness with dynamic pricing and uptake.

Through the dynamicpv::dynpv() function, the package provides calculations of the present values of costs, life years, QALYs or other payoffs allowing for dynamic uptake (also known as multiple cohorts) and dynamic pricing (also known as life-cycle). The starting point is a conventional cohort cost-effectiveness model, such as one computed using the heemod package.

Installation

You can install the development version of dynamicpv from GitHub as follows. (The package was previously known as dynacem, but dynamicpv better reflects the package’s intent.)

# Install pak package if not already installed
install.packages("pak")

# Install dynamicpv using pak, from MSD's dynacem repository
pak::pak("MSDLLCpapers/dynacem")

You should then load the package, alongside some other packages used here.

# Load the dynamicpv package
library(dynamicpv)

# Recommended others
library(dplyr)
library(heemod)
library(ggplot2)
library(tidyr)

How to use

There are three vignettes provided.

  1. The Dynamic Pricing vignette (vignette("Dynamic Pricing")) describes how present values may be calculated in the package from a payoff vector, allowing for the prices of the resources costed to be dynamic.

  2. The Dynamic Uptake vignette (vignette("Dynamic Uptake")) explores further how present values can be derived allowing for dynamic uptake. This is in contrast to the non-dynamic approach of calculating a present value for a single cohort of patients. This is analogous to the use by general insurance actuaries of run-off triangles.

  3. Finally, the Cost-Effectiveness Applications (vignette(Cost-Effectiveness Applications")) vignette describes how, given a static cost-effectiveness model (single cohort, prices constant in real terms), Incremental Cost-Effectiveness Ratios may be calculated that allow for dynamic pricing and/or dynamic uptake. This is illustrated by taking an example three-state partitioned survival model of a new intervention for an oncology indication compared to standard of care, with stated assumptions for how pricing and uptake may be dynamic. Nominal and Real ICERs are plotted over time, illustrating the impact of the loss of exclusivity points for each intervention.